12 papers
Local Minima in Quadratic-Penalty Relaxations of Binary Linear Programs
Cheng-Han Huang, Yongliang Sun, Chaoyan Huang +2
Many combinatorial optimization problems admit quadratic unconstrained binary formulations (QUBO) which can often be relaxed to the box and optimized using scalable gradi…
Trajectory Constraints for Imaging Inverse Problems
Chaoyan Huang, Haijie Yuan, Saiprasad Ravishankar +1
Diffusion models have achieved strong performance in imaging inverse problems, but typically rely on domain-matched pretrained models and external training data. Moreover, errors i…
A Principled Self-Referenced Early Stopping Approach for Deep Image Prior
Chaoyan Huang, Cheng-Han Huang, Ismail R. Alkhouri +1
Recently, Deep Image Prior (DIP) has demonstrated strong capabilities for solving inverse imaging problems (IIPs) by optimizing a randomly initialized convolutional neural network…
Fractional-gradient Sparsity with Autoencoding Sequential Deep Image Prior for 3D CT Reconstruction
Haijie Yuan, Chaoyan Huang, Srijita Bandopadhyay +2
3D volumetric reconstruction from incomplete or noisy measurements is a fundamental problem in medical imaging and computational tomography. Deep image prior (DIP)-based methods ha…
Dynamic MRI Reconstruction Via Dual Deep Priors and Low-Rank Plus Sparse Modeling
Yongliang Sun, Siddhant Gautam, Chaoyan Huang +3
Dynamic MRI reconstruction from undersampled measurements is a challenging inverse problem that requires preserving both spatial reconstruction quality and temporal consistency acr…
Frequency Error-Guided Under-sampling Optimization for Multi-Contrast MRI Reconstruction
Xinming Fang, Chaoyan Huang, Juncheng Li +3
Magnetic resonance imaging (MRI) plays a vital role in clinical diagnostics, yet it remains hindered by long acquisition times and motion artifacts. Multi-contrast MRI reconstructi…
Inertial Proximal Difference-of-Convex Algorithm with Convergent Bregman Plug-and-Play for Nonconvex Imaging
Tsz Ching Chow, Chaoyan Huang, Zhongming Wu +2
Imaging tasks are typically tackled using a structured optimization framework. This paper delves into a class of algorithms for difference-of-convex (DC) structured optimization, f…
Deep Block Proximal Linearised Minimisation Algorithm for Non-convex Inverse Problems
Chaoyan Huang, Zhongming Wu, Yanqi Cheng +3
Image restoration is typically addressed through non-convex inverse problems, which are often solved using first-order block-wise splitting methods. In this paper, we consider a ge…
Extrapolated Plug-and-Play Three-Operator Splitting Methods for Nonconvex Optimization with Applications to Image Restoration
Zhongming Wu, Chaoyan Huang, Tieyong Zeng
This paper investigates the convergence properties and applications of the three-operator splitting method, also known as Davis-Yin splitting (DYS) method, integrated with extrapol…
Edge-guided Low-light Image Enhancement with Inertial Bregman Alternating Linearized Minimization
Chaoyan Huang, Zhongming Wu, Tieyong Zeng
Prior-based methods for low-light image enhancement often face challenges in extracting available prior information from dim images. To overcome this limitation, we introduce a sim…
Dynamic Multimodal Information Bottleneck for Multimodality Classification
Yingying Fang, Shuang Wu, Sheng Zhang +5
Effectively leveraging multimodal data such as various images, laboratory tests and clinical information is gaining traction in a variety of AI-based medical diagnosis and prognosi…
Spherical Image Inpainting with Frame Transformation and Data-driven Prior Deep Networks
Jianfei Li, Chaoyan Huang, Raymond Chan +3
Spherical image processing has been widely applied in many important fields, such as omnidirectional vision for autonomous cars, global climate modelling, and medical imaging. It i…